MRI criteria for the diagnosis of multiple sclerosis: MAGNIMS consensus guidelines

Neurosarcoidosis presenting as longitudinally extensive myelitis: Diagnostic assessment, differential diagnosis, and therapeutic approach

Neurosarcoidosis is an uncommon and multiform clinical entity. Its presentation as an isolated longitudinal extensive transverse myelitis (LETM) is rare and challenging to identify. We report a case of LETM in a 60-year-old patient with no significant systemic symptoms nor relevant medical history. The peculiar spinal magnetic resonance imaging finding characterized by a posterior and central canal subpial contrast enhancement, the so-called “trident sign,” together with chest computed tomography scan and lymph node biopsy led to the diagnosis of sarcoidosis. We also discuss the main differential diagnoses of LETM and therapeutic options for sarcoidosis-related myelitis.

Relevance of Pathogenetic Mechanisms to Clinical Effectiveness of B-Cell-Depleting Monoclonal Antibodies in Multiple Sclerosis

Evidence of the effectiveness of B-cell-depleting monoclonal antibodies (mAbs) in multiple sclerosis (MS) prompted a partial revisitation of the pathogenetic paradigm of the disease, which was, so far, considered a T-cell-mediated autoimmune disorder. Mechanisms underlying the efficacy of B-cell-depleting mAbs in MS are still unknown. However, they likely involve the impairment of pleiotropic B-cell functions different from antibody secretion, such as their role as antigen-presenting cells during both the primary immune response in the periphery and the secondary response within the central nervous system (CNS). A potential impact of B-cell-depleting mAbs on inflammation compartmentalised within the CNS was also suggested, but little is known about the mechanism underlying this latter phenomenon as no definite evidence was provided so far on the ability of mAbs to cross the blood–brain barrier and reliable biomarkers of compartmentalised inflammation are lacking. The present paper briefly summarises the immunopathogenesis of MS with a focus on onset of autoimmunity and compartmentalisation of the immune response; mechanisms mediating B-cell depletion and underlying the effectiveness of B-cell-depleting mAbs are also discussed.

Prediction of Conversion from CIS to Clinically Definite Multiple Sclerosis Using Convolutional Neural Networks

Multiple sclerosis (MS) is a chronic neurological disease of the central nervous system (CNS). Early diagnosis of MS is highly desirable as treatments are more effective in preventing MS-related disability when given in the early stages of the disease. The main aim of this research is to predict the occurrence of a second MS-related clinical event, which indicates the conversion of clinically isolated syndrome (CIS) to clinically definite MS (CDMS). In this study, we apply a branch of artificial intelligence known as deep learning and develop a fully automated algorithm primed with convolutional neural network (CNN) that has the ability to learn from MRI scan features. The basic architecture of our algorithm is that of the VGG16 CNN model, but amended such that it can handle MRI DICOM images. A dataset comprised of scans acquired using two different scanners was used for the purposes of verification of the algorithm. A group of 49 patients had volumetric MRI scans taken at onset of the disease and then again one year later using one of the two scanners. In total, this yielded 7360 images which were then used for training, validation, and testing of the algorithm. Initially, these raw images were taken through 4 steps of preprocessing. In order to boost the efficiency of the process, we pretrained our algorithm using the publicly available ADNI dataset used to classify Alzheimer's disease. Finally, we used our preprocessed dataset to train and test the algorithm. Clinical evaluation conducted a year after the first time point revealed that 26 of the 49 patients had converted to CDMS, while the remaining 23 had not. Results of testing showed that our algorithm was able to predict the clinical results with an accuracy of 88.8% and with an area under the curve (AUC) of 91%. A highly accurate algorithm was developed using CNN approach to reliably predict conversion of patients with CIS to CDMS using MRI data from two different scanners.

Quantitative susceptibility mapping versus phase imaging to identify multiple sclerosis iron rim lesions with demyelination

BACKGROUND AND PURPOSE

To compare quantitative susceptibility mapping (QSM) and high-pass-filtered (HPF) phase imaging for (1) identifying chronic active rim lesions with more myelin damage and (2) distinguishing patients with increased clinical disability in multiple sclerosis.

METHODS

Eighty patients were scanned with QSM for paramagnetic rim detection and Fast Acquisition with Spiral Trajectory and T2prep for myelin water fraction (MWF). Chronic lesions were classified based on the presence/absence of rim on HPF and QSM images. A lesion-level linear mixed-effects model with MWF as the outcome was used to compare myelin damage among the lesion groups. A multiple patient-level linear regression model was fit to establish the association between Expanded Disease Status Scale (EDSS) and the log of the number of rim lesions.

RESULTS

Of 2062 lesions, 188 (9.1%) were HPF rim+/QSM rim+, 203 (9.8%) were HPF rim+/QSM rim-, and the remainder had no rim. In the linear mixed-effects model, HPF rim+/QSM rim+ lesions had significantly lower MWF than both HPF rim+/QSM rim- (p < .001) and HPF rim-/QSM rim- (p < .001) lesions, while the MWF difference between HPF rim+/QSM rim- and HPF rim-/QSM rim- lesions was not statistically significant (p = .130). Holding all other factors constant, the log number of QSM rim+ lesion was associated with EDSS increase (p = .044). The association between the log number of HPF rim+ lesions and EDSS was not statistically significant (p = .206).

CONCLUSIONS

QSM identifies paramagnetic rim lesions that on average have more myelin damage and stronger association with clinical disability than those detected by phase imaging.

Improved detection of multiple sclerosis lesions with T2-prepared double inversion recovery at 3T

BACKGROUND AND PURPOSE

Double inversion recovery (DIR) imaging is used in multiple sclerosis (MS) clinical protocols to improve the detection of cortical and juxtacortical gray matter lesions by nulling confounding signals originating from the cerebrospinal fluid and white matter. Achieving a high isotropic spatial resolution, to depict the neocortex and its typically small lesions, is challenged by the reduced signal-to-noise ratio (SNR) determined by multiple tissue signal nulling. Here, we evaluate both conventional and optimized DIR implementations to improve tissue contrast (TC), SNR, and MS lesion conspicuity.

METHODS

DIR images were obtained from MS patients and healthy controls using both conventional and prototype implementations featuring a T2-preparation module (T2P), to improve SNR and TC, as well as an image reconstruction routine with iterative denoising (ID). We obtained quantitative measures of SNR and TC, and evaluated the visibility of MS cortical, cervical cord, and optic nerve lesions in the different DIR images.

RESULTS

DIR implementations adopting T2P and ID enabled improving the SNR and TC of conventional DIR. In MS patients, 34% of cortical, optic nerve, and cervical cord lesions were visible only in DIR images acquired with T2P, and not in conventional DIR images. In the studied cases, image reconstruction with ID did not improve lesion conspicuity.

CONCLUSIONS

DIR with T2P should be preferred to conventional DIR imaging in protocols studying MS patients, as it improves SNR and TC and determines an improvement in cortical, optic nerve, and cervical cord lesion conspicuity.

Brain disconnectome mapping derived from white matter lesions and serum neurofilament light levels in multiple sclerosis: A longitudinal multicenter study

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Individual disconnectome maps generated using a template of 7T MRI data.

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Disconnectome maps conceptualize distal brain network aberrations.

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Using lesions maps from our MS cohort, we produced individual disconnectome maps.

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Serum neurofilament light levels were associated with disconnectome maps.

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Voxel-wise analyses revealed interesting association with serum neurofilament light levels.

Background and Objectives

Connectivity-based approaches incorporating the distribution and magnitude of the extended brain network aberrations caused by lesions may offer higher sensitivity for axonal damage in patients with multiple sclerosis (MS) than conventional lesion characteristics. Using individual brain disconnectome mapping, we tested the longitudinal associations between putative imaging-based brain network aberrations and levels of serum neurofilament light chain (NfL) as a neuroaxonal injury biomarker.

Methods

MS patients (n = 312, mean age 42.9 years, 71 % female) and healthy controls (HC) (n = 59, mean age 39.9 years, 78 % female) were prospectively enrolled at four European MS centres, and reassessed after two years (MS, n = 242; HC, n = 30). Post-processing of 3 Tesla (3 T) MRI data was performed at one centre using a harmonized pipeline, and disconnectome maps were calculated using BCBtoolkit based on individual lesion maps. Global disconnectivity (GD) was defined as the average disconnectome probability in each patient’s white matter. Serum NfL concentrations were measured by single molecule array (Simoa). Robust linear mixed models (rLMM) with GD or T2-lesion volume (T2LV) as dependent variables, patient as a random factor, serum NfL, age, sex, timepoint for visit, diagnosis, treatment, and center as fixed factors were run.

Results

rLMM revealed significant associations between GD and serum NfL (t = 2.94, p = 0.003), age (t = 4.21, p = 2.5 × 10⁻⁵), and longitudinal changes in NfL (t = -2.29, p = 0.02), but not for sex (t = 0.63, p = 0.53) or treatments (t = 0.80–0.83, p = 0.41–0.42). Voxel-wise analyses revealed significant associations between dysconnectivity in cerebellar and brainstem regions and serum NfL (t = 7.03, p < 0.001).

Discussion

In our prospective multi-site MS cohort, rLMMs demonstrated that the extent of global and regional brain disconnectivity is sensitive to a systemic biomarker of axonal damage, serum NfL, in patients with MS. These findings provide a neuroaxonal correlate of advanced disconnectome mapping and provide a platform for further investigations of the functional and potential clinical relevance of brain disconnectome mapping in patients with brain disorders.

IL-10 Gene Polymorphisms and IL-10 Serum Levels in Patients with Multiple Sclerosis in Lithuania

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system with features of demyelination and axonal degeneration at a young age. Genetic factors may play an important role in the development of multiple sclerosis. (1) Objective: To investigate IL-10 rs1800871, rs1800872, rs1800896, and IL-10 serum levels in patients with multiple sclerosis. (2) Methods: Our study included patients with multiple sclerosis (n = 127) and healthy volunteers (n = 195). The subjects’ DNA was extracted from peripheral blood leukocytes and genotyped by real-time polymerase chain reaction. The results were analyzed using the program “IBM SPSS Statistics 27.0”. (3) Results: The IL-10 SNPs were analyzed between the MS and control groups; however, no statistically significant results were found. The serum levels of IL-10 in the groups of MS and healthy subjects were not statistically significantly different (median (IQR): 0.828 (1.533) vs. 0.756 (0.528), p = 0.872). (4) Conclusions: IL-10 rs1800871, rs1800872, and rs1800896 and serum IL-10 levels are not likely to be associated with MS development. However, individuals carrying the rare haplotypes of rs1800871, rs1800872, and rs1800896 were associated with increased odds of MS (p = 0.006).

Lesion size and shape in central vein sign assessment for multiple sclerosis diagnosis: An in vivo and postmortem MRI study

BACKGROUND

The "central vein sign" (CVS), a linear hypointensity on T2*-weighted imaging corresponding to a central vein/venule, is associated with multiple sclerosis (MS) lesions. The effect of lesion-size exclusion criteria on MS diagnostic accuracy has not been extensively studied.

OBJECTIVE

Investigate the optimal lesion-size exclusion criteria for CVS use in MS diagnosis.

METHODS

Cross-sectional study of 163 MS and 51 non-MS, and radiological/histopathological correlation of 5 MS and 1 control autopsy cases. The effects of lesion-size exclusion on MS diagnosis using the CVS, and intralesional vein detection on histopathology were evaluated.

RESULTS

CVS+ lesions were larger compared to CVS- lesions, with effect modification by MS diagnosis (mean difference +7.7 mm³, p = 0.004). CVS percentage-based criteria with no lesion-size exclusion showed the highest diagnostic accuracy in differentiating MS cases. However, a simple count of three or more CVS+ lesions greater than 3.5 mm is highly accurate and can be rapidly implemented (sensitivity 93%; specificity 88%). On magnetic resonance imaging (MRI)-histopathological correlation, the CVS had high specificity for identifying intralesional veins (0/7 false positives).

CONCLUSION

Lesion-size measures add important information when using CVS+ lesion counts for MS diagnosis. The CVS is a specific biomarker corresponding to intralesional veins on histopathology.

Nonlesional Sources of Contrast Enhancement on Postgadolinium "Black-Blood" 3D T1-SPACE Images in Patients with Multiple Sclerosis

BACKGROUND AND PURPOSE

We hypothesized that 3D T1-TSE "black-blood" images may carry an increased risk of contrast-enhancing lesion misdiagnosis in patients with MS because of the misinterpretation of intraparenchymal vein enhancement. Thus, the occurrence of true-positive and false-positive findings was compared between standard MPRAGE and volumetric interpolated brain examination techniques.

MATERIALS AND METHODS

Sampling perfection with application-optimized contrasts by using different flip-angle evolution (SPACE) images obtained from 232 patients with MS, clinically isolated syndrome, or radiologically isolated syndrome were compared with standard MPRAGE and volumetric interpolated brain examination images. The intraparenchymal vein contrast-to-noise ratio was estimated at the level of the thalami. Contrast-enhancing lesions were blindly detected by 2 expert readers and 1 beginner reader. True- and false-positives were determined by senior readers' consensus. True-positive and false-positive frequency differences and patient-level diagnosis probability were tested with the McNemar test and OR. The contrast-to-noise ratio and morphology were compared using the Mann-Whitney U and χ² tests.

RESULTS

The intraparenchymal vein contrast-to-noise ratio was higher in SPACE than in MPRAGE and volumetric interpolated brain examination images (P < .001, both). There were 66 true-positives and 74 false-positives overall. SPACE detected more true-positive and false-positive results (P range < .001-.07) but did not increase the patient's true-positive likelihood (OR = 1 1.29, P = .478-1). However, the false-positive likelihood was increased (OR = 3.03-3.55, P = .008-.027). Venous-origin false-positives (n = 59) with contrast-to-noise ratio and morphology features similar to small-sized (≤14 mm³ P = .544) true-positives occurred more frequently in SPACE images (P < .001).

CONCLUSIONS

Small intraparenchymal veins may confound the diagnosis of enhancing lesions on postgadolinium black-blood SPACE images.

Role of artificial intelligence in MS clinical practice

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For medical applications, machine learning (including deep learning) are the most commonly used artificial intelligence (AI) approaches.

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It can improve multiple sclerosis (MS) diagnosis, prognostication and treatment monitoring.

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Thanks to AI, MRI and cognitive phenotypes of MS patients were identified.

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AI can shorten MRI protocols for MS, allowing the application of advanced techniques.

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It can reduce the human effort for MRI analysis, especially for lesion segmentation.

Machine learning (ML) and its subset, deep learning (DL), are branches of artificial intelligence (AI) showing promising findings in the medical field, especially when applied to imaging data. Given the substantial role of MRI in the diagnosis and management of patients with multiple sclerosis (MS), this disease is an ideal candidate for the application of AI techniques. In this narrative review, we are going to discuss the potential applications of AI for MS clinical practice, together with their limitations. Among their several advantages, ML algorithms are able to automate repetitive tasks, to analyze more data in less time and to achieve higher accuracy and reproducibility than the human counterpart. To date, these algorithms have been applied to MS diagnosis, prognosis, disease and treatment monitoring. Other fields of application have been improvement of MRI protocols as well as automated lesion and tissue segmentation. However, several challenges remain, including a better understanding of the information selected by AI algorithms, appropriate multicenter and longitudinal validations of results and practical aspects regarding hardware and software integration. Finally, one cannot overemphasize the paramount importance of human supervision, in order to optimize the use and take full advantage of the potential of AI approaches.

Demyelinating Syndromes in Systemic Lupus Erythematosus: Data From the "Attikon" Lupus Cohort

Background

The demyelinating syndromes of the central nervous system (CNS) that occur in the context of systemic lupus erythematosus (SLE) may represent a manifestation of neuropsychiatric lupus (NPSLE) or an overlap of SLE and multiple sclerosis (MS). The differential diagnosis between the two entities has important clinical implications because the therapeutic management differs.

Objectives

To characterize CNS demyelinating syndromes in a large SLE cohort as neuropsychiatric SLE (NPSLE) or SLE-MS overlap using a multidisciplinary approach and existing diagnostic (for MS) and classification criteria (for SLE).

Methods

Patients from the "Attikon" lupus cohort (n = 707) were evaluated for demyelinating syndromes. Clinical, laboratory, and neuroimaging data were recorded for each patient. Following multidisciplinary evaluation and application of criteria, the demyelinating syndrome was attributed to either SLE or MS. Patients with transverse myelitis were not included in this study.

Results

We identified 26 patients with demyelinating syndromes (3.7%). Of them, 12 were diagnosed as primary SLE-demyelination (46.2%) and 14 as overlap SLE-MS (53.8%). The two groups did not differ with respect to rheumatologic and neurologic manifestations or autoantibodies. SLE patients with demyelination manifested mild extra-CNS disease mainly involving joints and skin, while severe non-CNS manifestations were rare. However, these patients were less likely to have elevated IgG index (OR 0.055 95% CI: 0.008-0.40) and positive oligoclonal bands (OR 0.09 95% CI: 0.014-0.56), as well as brain lesions in the spinal cord, infratentorial, periventricular, and juxtacortical regions. A single brain region was affected in 9 patients with SLE-demyelination (75%), while all patients with MS-SLE had multiple affected brain regions. MS-SLE overlap was associated with an increased likelihood of neurologic relapses (OR 18.2, 95% CI: 1.76-188), while SLE-demyelination patients were less likely to exhibit neurological deficits (EDSS >0) at the last follow-up visit (50 vs. 78.6% in SLE-MS, respectively).

Conclusions

Demyelination in the context of SLE follows a more benign course compared to a frank SLE-MS overlap. Extension of follow-up will ascertain whether patients with SLE-demyelination evolve to MS, or this is a bona fide NPSLE syndrome.

Reproducibility of Lesion Count in Various Subregions on MRI Scans in Multiple Sclerosis

Purpose

Lesion number and burden can predict the long-term outcome of multiple sclerosis, while the localization of the lesions is also a good predictive marker of disease progression. These biomarkers are used in studies and in clinical practice, but the reproducibility of lesion count is not well-known.

Methods

In total, five raters evaluated T2 hyperintense lesions in 140 patients with multiple sclerosis in six localizations: periventricular, juxtacortical, deep white matter, infratentorial, spinal cord, and optic nerve. Black holes on T1-weighted images and brain atrophy were subjectively measured on a binary scale. Reproducibility was measured using the intraclass correlation coefficient (ICC). ICCs were also calculated for the four most accurate raters to see how one outlier can influence the results.

Results

Overall, moderate reproducibility (ICC 0.5-0.75) was shown, which did not improve considerably when the most divergent rater was excluded. The areas that produced the worst results were the optic nerve region (ICC: 0.118) and atrophy judgment (ICC: 0.364). Comparing high- and low-lesion burdens in each region revealed that the ICC is higher when the lesion count is in the mid-range. In the periventricular and deep white matter area, where lesions are common, higher ICC was found in patients who had a lower lesion count. On the other hand, juxtacortical lesions and black holes that are less common showed higher ICC when the subjects had more lesions. This difference was significant in the juxtacortical region when the most accurate raters compared patients with low (ICC: 0.406 CI: 0.273-0.546) and high (0.702 CI: 0.603-0.785) lesion loads.

Conclusion

Lesion classification showed high variability by location and overall moderate reproducibility. The excellent range was not achieved, owing to the fact that some areas showed poor performance. Hence, putting effort toward the development of artificial intelligence for the evaluation of lesion burden should be considered.

Low Contrast Visual Evoked Potentials for Early Detection of Optic Neuritis

Optic neuritis (ON) detection is important for the early diagnosis and management of multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD). However, the conventional high-contrast visual evoked potential (VEP) used for ON detection lacks sensitivity for identifying ON presenting as mild or unremarkable visual disturbance, which is common in first-episode ON. Therefore, this study aimed to investigate whether a change in contrast or check size improves the sensitivity of VEP to first-ever ON. In total, 60 patients with the demyelinating disease (29 MS and 31 idiopathic patients with ON) without ON or with first-ever ON at least 6 months prior and 32 healthy controls underwent neuro-ophthalmic evaluations. VEPs were induced using three pattern-reversal checkerboard stimuli having, respectively, 10% contrast with a check size of 32' (LC32 VEP), 100% contrast with a check size of 32' (HC32 VEP; conventional VEP), and 100% contrast with a check size of 16' (HC16 VEP). The receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) were calculated to determine the most appropriate VEP method for detecting optic nerve involvement. The optimal cut-off point was determined using the Youden index (J-index). The McNemar test was used to determine whether dichotomous proportions were equivalent. In comparison with first-ever ON eyes (n = 39) and healthy eyes (n = 64), LC32 VEP showed the highest AUC for discriminating ON (0.750, p < 0.001; 0.730 for HC32 VEP, p < 0.001; 0.702 for HC16 VEP, p = 0.001). In the first-ever ON group, LC32 VEP and conventional HC32 VEP were abnormal in 76.9 and 43.6%, respectively (McNemar, p < 0.001), and combining these tests did not improve sensitivity. These indicate that LC32 VEP is the most sensitive method for detecting first-ever ON. Visual evoked potential with 10% contrast stimuli was superior to conventional VEP for detecting first-ever ON. Thus, adding these LC stimuli might be helpful in identifying optic nerve involvement in ON with mild or unremarkable visual impairment.

Kappa Free Light Chains, Soluble Interleukin-2 Receptor, and Interleukin-6 Help Explore Patients Presenting With Brain White Matter Hyperintensities

Introduction

Many patients are referred to multiple sclerosis (MS) tertiary centers to manage brain white matter hyperintensities (WMH). Multiple diagnoses can match in such situations, and we lack proper tools to diagnose complex cases.

Objective

This study aimed to prospectively analyze and correlate with the final diagnosis, cerebrospinal fluid (CSF) interleukin (IL)-1β, soluble IL-2 receptor (CD25), IL-6, IL-10, and kappa free light chains (KFLC) concentrations in patients presenting with brain WMH.

Methods

All patients over 18 years addressed to our MS tertiary center for the diagnostic workup of brain WMH were included from June 1, 2020, to June 1, 2021. Patients were separated into three groups—MS and related disorder (MSARD), other inflammatory neurological disorder (OIND), and non-inflammatory neurological disorder (NIND) groups—according to clinical presentation, MRI characteristics, and biological workup.

Results

A total of 176 patients (129 women, mean age 45.8 ± 14.7 years) were included. The diagnosis was MSARD (n = 88), OIND (n = 35), and NIND (n = 53). Median CSF KFLC index and KFLC intrathecal fraction (IF) were higher in MSARD than in the OIND and NIND groups; p < 0.001 for all comparisons. CSF CD25 and IL-6 concentrations were higher in the OIND group than in both the MSARD and NIND groups; p < 0.001 for all comparisons. KFLC index could rule in MSARD when compared to NIND (sensitivity, 0.76; specificity, 0.91) or OIND (sensitivity, 0.73; specificity, 0.76). These results were similar to those with oligoclonal bands (sensitivity, 0.59; specificity, 0.98 compared to NIND; sensitivity, 0.59; specificity, 0.88 compared to OIND). In contrast, elevated CSF CD25 and IL-6 could rule out MSARD when compared to OIND (sensitivity, 0.58 and 0.88; specificity, 0.95 and 0.74, respectively).

Discussion

Our results show that, as OCBs, KFLC biomarkers are helpful tools to rule in MSARD, whereas elevated CSF CD25 and IL-6 rule out MSARD. Interestingly, CSF IL-6 concentration could help identify neuromyelitis optica spectrum disorder, myelin oligodendrocyte glycoprotein antibody-associated disease, and central nervous system (CNS) vasculitis. These results need to be confirmed within more extensive and multicentric studies. Still, they sustain that KFLC, CSF CD25, and CSF IL-6 could be reliable biomarkers in brain WMH diagnostic workup for differentiating MSARD from other brain inflammatory MS mimickers.

Case Report Multiple Sclerosis

BACKGROUND: Multiple sclerosis (MS) is an autoimmune disease in the form of chronic inflammation of the CNS. This disease is mediated by autoreactive lymphocytes that can cross the blood-brain barrier and thus enter the CNS and cause inflammation. Chronic demyelinating CNS lesions characterize multiple sclerosis, and immunity to myelin is involved. This disease predominantly attacks the brain, spinal cord, and optic nerve. The diagnosis of MS is made clinically, and there is no single definitive test for MS. The key to diagnosis is Dissemination in Space (DIS) and Dissemination in Time (DIT). Magnetic resonance imaging has become an essential part of the diagnosis of MS after clinical. CASE REPORT: Here, we report a case of a 31 year-old woman with the main complaint of weakness of four extremities accompanied by a decreased vision and impaired urination and bowel movement. The patient was diagnosed with suspected MS. CONCLUSION: The patient subsequently was treated with intravenous steroids and, on the routine follow-up found marked clinical improvement.

3-Dimensional Fluid and White Matter Suppression Magnetic Resonance Imaging Sequence Accelerated With Compressed Sensing Improves Multiple Sclerosis Cervical Spinal Cord Lesion Detection Compared With Standard 2-Dimensional Imaging

OBJECTIVES

Fluid and white matter suppression (FLAWS) is a recently proposed magnetic resonance sequence derived from magnetization-prepared 2 rapid acquisition gradient-echo providing 2 coregistered datasets with white matter- and cerebrospinal fluid-suppressed signal, enabling synthetic imaging with amplified contrast. Although these features are high potential for brain multiple sclerosis (MS) imaging, spinal cord has never been evaluated with this sequence to date. The objective of this work was therefore to assess diagnostic performance and self-confidence provided by compressed-sensing (CS) 3-dimensional (3D) FLAWS for cervical MS lesion detection on a head scan that includes the cervical cord without changing standard procedures.

MATERIALS AND METHODS

Prospective 3 T scans (MS first diagnosis or follow-up) acquired between 2019 and 2020 were retrospectively analyzed. All patients underwent 3D CS-FLAWS (duration: 5 minutes 40 seconds), axial T2 turbo spin echo covering cervical spine from cervicomedullary junction to the same inferior level as FLAWS, and sagittal cervical T2/short tau inversion recovery imaging. Two readers performed a 2-stage double-blind reading, followed by consensus reading. Wilcoxon tests were used to compare the number of detected spinal cord lesions and the reader's diagnostic self-confidence when using FLAWS versus the reference 2D T2-weighted imaging.

RESULTS

Fifty-eight patients were included (mean age, 40 ± 13 years, 46 women, 7 ± 6 years mean disease duration). The CS-FLAWS detected significantly more lesions than the reference T2-weighted imaging (197 vs 152 detected lesions, P < 0.001), with a sensitivity of 98% (T2-weighted imaging sensitivity: 90%) after consensual reading. Considering the subgroup of patients who underwent sagittal T2 + short tau inversion recovery imaging (Magnetic Resonance Imaging for Multiple Sclerosis subgroup), +250% lesions were detected with FLAWS (63 vs 25 lesions detected, P < 0.001). Mean reading self-confidence was significantly better with CS-FLAWS (median, 5 [interquartile range, 1] [no doubt for diagnosis] vs 4 [interquartile range, 1] [high confidence]; P < 0.001).

CONCLUSIONS

Imaging with CS-FLAWS provides an improved cervical spinal cord exploration for MS with increased self-confidence compared with conventional T2-weighted imaging, in a clinically acceptable time.

[Acute disseminated encephalomyelitis]

Hintergrund

Die akute disseminierte Enzephalomyelitis (ADEM) gehört zu den seltenen demyelinisierenden Erkrankungen, die meistens bei Kindern auftreten. ADEM gehört laut Leitlinien zu den Myelin-Oligodendrozyten-Glykoprotein(MOG)-assoziierten Krankheiten und manifestiert sich in der Regel nach febrilen Infektionen (auch nach SARS-CoV-2) oder, deutlich seltener, nach Impfungen.

Fragestellung

Inzidenz, Verlauf und klinische sowie radiologische Diagnostik sowie Entwicklung und Therapieoptionen von ADEM.

Material und Methode

Analyse und Auswertung der Literatur über ADEM sowie Analyse der bemerkenswerten Fälle und Leitlinien.

Ergebnisse

Zu den ersten Anzeichen von ADEM gehören Fieber, Nausea bis zum Erbrechen sowie Kopfschmerzen und Meningismus sowie per definitionem eine Enzephalopathie, die am Anfang wenig ausgeprägt sein kann und sich meistens als Schläfrigkeit und Verwirrung manifestiert. Die radiologische Diagnose wird in der Magnetresonanztomographie (MRT) gestellt. Hier sind asymmetrisch verteilte, unscharf abgrenzbare, tumorsimulierende Läsionen supra- und infratentoriell abgrenzbar. In der akuten Phase nehmen die Läsionen meistens ringförmig Kontrastmittel auf und zeigen eine Diffusionsrestriktion. Spinaler Befall der grauen Substanz mit dem typischen H‑Muster mit Myelitis transversa ist nicht selten. Die ADEM hat meistens einen monophasischen Verlauf, wobei eine rekurrierende Form („relapsing ADEM“) in 1–20 % der Fälle zu erwarten ist. Bei der Behandlung kommen Steroide und in schweren Fällen Immunsuppressiva zum Einsatz.

Schlussfolgerung

ADEM ist eine meist monophasische Erkrankung, deren Symptome nach einigen Wochen/Monaten abklingen sollten. Es ist wichtig, sie von anderen demyelinisierenden Krankheiten wie der multiplen Sklerose zu unterscheiden, um die nötige Therapie nicht zu verzögern.

Magnetic resonance imaging criteria at onset to differentiate pediatric multiple sclerosis from acute disseminated encephalomyelitis: A nationwide cohort study

BACKGROUND

MRI of the nervous system is the critical in distinguishing pediatric MS from acute disseminated encephalomyelitis (ADEM). Our aim was to propose MRI criteria to distinguish MS from monophasic ADEM based on the first MRI and to validate previously proposed MRI criteria.

METHODS

A neuroradiologist undertook retrospective evaluation of the MRI at the first demyelinating event in children (<18 years) with medical record-validated MS and ADEM in Denmark during 2008-15. We used forward stepwise logistic regression to identify MRI categories that differed significantly between MS and ADEM. We estimated accuracy statistics for all MRI criteria to distinguish MS from ADEM.

RESULTS

The monophasic ADEM cohort (n=46) was nationwide and population-based during 2008-15; the median age at onset of 5.3 years (range 0.8‒17.2) and children had at least five years of follow-up to ensure a monophasic disease course. Children with MS (n=67) had a median age at onset of 16.3 years (range 3.3‒17.9). Having at least two categories best distinguished MS from monophasic ADEM by an area under the curve of 83% to 89%: (a) corpus callosum long axis perpendicular lesion; (b) only well-defined lesions; (c) absence of basal ganglia or thalamus lesion OR, (a) corpus callosum long axis perpendicular lesion; (b) only well-defined lesions; (c) absence of diffuse large lesions; (d) black holes. The Callen, KIDMUS, and IPMSSG criteria performed well. The McDonald 2017, Barkhof, MAGNIMS, and Verhey criteria had poorer performance.

CONCLUSION

This study provides Class II evidence that MRI has good performance in differentiating MS from monophasic ADEM at onset.

Experimental laboratory biomarkers in multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is a chronic autoimmune disorder of the central nervous system; the cause of this condition remains unknown. Researchers have analyzed different biomarkers related to MS. Here, experimental laboratory biomarkers for MS are identified and analyzed.

METHODS

The current study examined articles investigating biomarkers for MS. Records were obtained from the PubMed, LILACS, and EBSCO databases using an identical search strategy and terms that included "multiple sclerosis," "MS," and "biomarkers." In the current review, we also focus on lesser known biomarkers that have not yet been established for use in clinical practice.

RESULTS

Previous studies have explored molecular substances that may help diagnose MS and manage its adverse effects. Commonly studied factors include neurofilaments, sCD163, CXCL13, NEO, NF‑L, OPN, B cells, T cells, and integrin-binding proteins.

CONCLUSIONS

Interactions between environmental and genetic factors have been implicated in the development of MS. Previous investigations have identified a wide range of biomarkers that can be used for diagnosis and disease management. These molecules and their associated studies provide vital insight and data to help primary physicians improve clinical and health outcomes for MS patients.

Automatic segmentation of white matter hyperintensities: validation and comparison with state-of-the-art methods on both Multiple Sclerosis and elderly subjects

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Automatic segmentation of MS lesions and age-related WMH from 3D T1 and T2-FLAIR.

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Comparison to consensus show improved performance of WHASA-3D compared to WHASA.

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WHASA-3D outperforms available state-of-the-art methods with their default settings.

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WHASA-3D could be a useful tool for clinical practice and clinical trials.

Different types of white matter hyperintensities (WMH) can be observed through MRI in the brain and spinal cord, especially Multiple Sclerosis (MS) lesions for patients suffering from MS and age-related WMH for subjects with cognitive disorders and/or elderly people. To better diagnose and monitor the disease progression, the quantitative evaluation of WMH load has proven to be useful for clinical routine and trials. Since manual delineation for WMH segmentation is highly time-consuming and suffers from intra and inter observer variability, several methods have been proposed to automatically segment either MS lesions or age-related WMH, but none is validated on both WMH types. Here, we aim at proposing the White matter Hyperintensities Automatic Segmentation Algorithm adapted to 3D T2-FLAIR datasets (WHASA-3D), a fast and robust automatic segmentation tool designed to be implemented in clinical practice for the detection of both MS lesions and age-related WMH in the brain, using both 3D T1-weighted and T2-FLAIR images. In order to increase its robustness for MS lesions, WHASA-3D expands the original WHASA method, which relies on the coupling of non-linear diffusion framework and watershed parcellation, where regions considered as WMH are selected based on intensity and location characteristics, and finally refined with geodesic dilation. The previous validation was performed on 2D T2-FLAIR and subjects with cognitive disorders and elderly subjects. 60 subjects from a heterogeneous database of dementia patients, multiple sclerosis patients and elderly subjects with multiple MRI scanners and a wide range of lesion loads were used to evaluate WHASA and WHASA-3D through volume and spatial agreement in comparison with consensus reference segmentations. In addition, a direct comparison on the MS database with six available supervised and unsupervised state-of-the-art WMH segmentation methods (LST-LGA and LPA, Lesion-TOADS, lesionBrain, BIANCA and nicMSlesions) with default and optimised settings (when feasible) was conducted. WHASA-3D confirmed an improved performance with respect to WHASA, achieving a better spatial overlap (Dice) (0.67 vs 0.63), a reduced absolute volume error (AVE) (3.11 vs 6.2 mL) and an increased volume agreement (intraclass correlation coefficient, ICC) (0.96 vs 0.78). Compared to available state-of-the-art algorithms on the MS database, WHASA-3D outperformed both unsupervised and supervised methods when used with their default settings, showing the highest volume agreement (ICC = 0.95) as well as the highest average Dice (0.58). Optimising and/or retraining LST-LGA, BIANCA and nicMSlesions, using a subset of the MS database as training set, resulted in improved performances on the remaining testing set (average Dice: LST-LGA default/optimized = 0.41/0.51, BIANCA default/optimized = 0.22/0.39, nicMSlesions default/optimized = 0.17/0.63, WHASA-3D = 0.58). Evaluation and comparison results suggest that WHASA-3D is a reliable and easy-to-use method for the automated segmentation of white matter hyperintensities, for both MS lesions and age-related WMH. Further validation on larger datasets would be useful to confirm these first findings.

Multi-lesion radiomics model for discrimination of relapsing-remitting multiple sclerosis and neuropsychiatric systemic lupus erythematosus

OBJECTIVES

To develop an MRI-based multi-lesion radiomics model for discrimination of relapsing-remitting multiple sclerosis (RRMS) and its mimicker neuropsychiatric systemic lupus erythematosus (NPSLE).

METHODS

A total of 112 patients with RRMS (n = 63) or NPSLE (n = 49) were assigned to training and test sets with a ratio of 3:1. All lesions across the whole brain were manually segmented on T2-weighted fluid-attenuated inversion recovery images. For each single lesion, 371 radiomics features were extracted and trained using machine learning algorithms, producing Radiomics Index for Lesion (RIL) for each lesion and a single-lesion radiomics model. Then, for each subject, single lesions were assigned to one of two disease courts based on their distance to decision threshold, and a Radiomics Index for Subject (RIS) was calculated as the mean RIL value of lesions on the higher-weighted court. Accordingly, a subject-level discrimination model was constructed and compared with performances of two radiologists.

RESULTS

The subject-based discrimination model satisfactorily differentiated RRMS and NPSLE in both training (AUC = 0.967, accuracy = 0.892, sensitivity = 0.917, and specificity = 0.872) and test sets (AUC = 0.962, accuracy = 0.931, sensitivity = 1.000, and specificity = 0.875), significantly better than the single-lesion radiomics method (training: p < 0.001; test: p = 0.001) Besides, the discrimination model significantly outperformed the senior radiologist in the training set (training: p = 0.018; test: p = 0.077) and the junior radiologist in both the training and test sets (training: p = 0.008; test: p = 0.023).

CONCLUSIONS

The multi-lesion radiomics model could effectively discriminate between RRMS and NPSLE, providing a supplementary tool for accurate differential diagnosis of the two diseases.

KEY POINTS

• Radiomic features of brain lesions in RRMS and NPSLE were different. • The multi-lesion radiomics model constructed using a merging strategy was comprehensively superior to the single-lesion-based model for discrimination of RRMS and NPSLE. • The RRMS-NPSLE discrimination model showed a significantly better performance or a trend toward significance than the radiologists.

Predictive MRI Biomarkers in MS—A Critical Review

Background and Objectives: In this critical review, we explore the potential use of MRI measurements as prognostic biomarkers in multiple sclerosis (MS) patients, for both conventional measurements and more novel techniques such as magnetization transfer, diffusion tensor, and proton spectroscopy MRI. Materials and Methods: All authors individually and comprehensively reviewed each of the aspects listed below in PubMed, Medline, and Google Scholar. Results: There are numerous MRI metrics that have been proven by clinical studies to hold important prognostic value for MS patients, most of which can be readily obtained from standard 1.5T MRI scans. Conclusions: While some of these parameters have passed the test of time and seem to be associated with a reliable predictive power, some are still better interpreted with caution. We hope this will serve as a reminder of how vast a resource we have on our hands in this versatile tool—it is up to us to make use of it.

Optic Nerve Lesion Length at the Acute Phase of Optic Neuritis Is Predictive of Retinal Neuronal Loss

Background and Objectives

Acute optic neuritis (ON) is a classical presenting symptom of multiple sclerosis (MS), neuromyelitis optica spectrum disorders (NMOSD), and anti–MOG-associated disorders. The resulting visual impairment is variable and can be severe. Clinicians are in need of predictive biomarkers to optimize the management of acute ON. In this longitudinal study (IRMANO, NCT03651662), we evaluated the ability of optic nerve lesion length measured on MRI at the acute phase of ON to predict retinal neuro-axonal loss and visual impairment at a chronic stage.

Methods

We conducted a longitudinal study (IRMANO, NCT03651662) of patients who presented a clinical episode of ON (≤8 weeks). All patients underwent a retinal optical coherence tomography (OCT) and a brain/optic nerve MRI, including 3D double-inversion recovery (DIR) sequence at the acute phase of ON and 12 months later. Primary outcomes were optic nerve DIR hypersignal lesion length, macular ganglion cell–inner plexiform layer (GCIPL) volume measured on OCT, and low-contrast monocular visual acuity (LCMVA).

Results

The study group included 51 patients (33 women, mean age of 32.4 years ± 7.9). We recruited patients with a clinically isolated syndrome (n = 20), a relapsing-remitting MS (n = 23), an isolated ON (n = 6), and a first clinical episode of NMOSD (n = 2). Optic nerve DIR hypersignal was observed in all but 1 symptomatic optic nerves. At inclusion, the mean optic nerve lesion length (in mm) was 12.35 ± 5.98. The mean GCIPL volume (in mm³) significantly decreased between inclusion (1.90 ± 0.18) and M₁₂ (1.67 ± 0.21; p < 0.0001). Optic nerve lesion length at inclusion was significantly associated with GCIPL thinning (estimate ± SD; −0.012 ± 0.004; p = 0.0016) and LCMVA at M₁₂ (0.016 ± 0.003; p < 0.001). Optic nerve lesion length significantly increased at M₁₂ (15.76 ± 8.70; p = 0.0007). The increase in optic nerve lesion length was significantly associated with the GCIPL thinning between inclusion and M₁₂ (−0.012 ± 0.003; p = 0.0011).

Discussion

At the acute phase of ON, optic nerve lesion length is an imaging biomarker predictive of retinal neuro-axonal loss and chronic visual impairment, which can help to stratify future therapeutic strategies in acute ON.

Classification of Evidence

This study provides Class I evidence that optic nerve lesion length measured on MRI during the acute phase of a first episode of ON is associated with long-term retinal neuro-axonal loss and visual impairment.

Central vein sign: A putative diagnostic marker for multiple sclerosis

The presence of a "central vein sign" (CVS) has been introduced as a biomarker for the diagnosis of multiple sclerosis (MS) and shown to have the ability to accurately differentiate MS from other white matter diseases (MS mimics). Following the development of susceptibility-based magnetic resonance venography that allowed the in vivo detection of CVS, a standard CVS definition was established by introducing the "40% rule" that assesses the number of MS lesions with CVS as a fraction of the total number of lesions to differentiate MS lesions from other types of lesions. The "50% rule," the "three-lesion criteria," and the "six-lesion criteria" were later introduced and defined. Each of these rules had high levels of sensitivity, specificity, and accuracy in differentiating MS from other diseases, which has been recognized by the Magnetic Resonance Imaging in MS (MAGNIMS) group and the Consortium of MS Centers task force. The North American Imaging in Multiple Sclerosis Cooperative even provided statements and recommendations aiming to refine, standardize and evaluate the CVS in MS. Herein, we review the existing literature on CVS and evaluate its added value in the diagnosis of MS and usefulness in differentiating it from other vasculopathies. We also review the histopathology of CVS and identify available automated CVS assessment methods as well as define the role of vascular comorbidities in the diagnosis of MS.

Neurologic Toxicity of Immune Checkpoint Inhibitors: A Review of Literature

Immune checkpoint inhibitors have entailed a change of paradigm in the management of multiple malignant diseases and are acquiring a key role in an increasing number of clinical sceneries. However, since their mechanism of action is not limited to the tumor microenvironment, their systemic activity may lead to a wide spectrum of immune-related side effects. Although neurological adverse events are much less frequent than gastrointestinal, hepatic, or lung toxicity, with an incidence of <5%, their potential severity and consequent interruptions to cancer treatment make them of particular importance. Despite them mainly implying peripheral neuropathies, immunotherapy has also been associated with an increased risk of encephalitis and paraneoplastic disorders affecting the central nervous system, often appearing in a clinical context where the appropriate diagnosis and early management of neuropsychiatric symptoms can be challenging. Although the pathogenesis of these complications is not fully understood yet, the blockade of tumoral inhibitory signals, and therefore the elicitation of cytotoxic T-cell-mediated response, seems to play a decisive role. The aim of this review was to summarize the current knowledge about the pathogenic mechanisms, clinical manifestations, and therapeutic recommendations regarding the main forms of neurotoxicity related to checkpoint inhibitors.

Neuroradiological differentiation of white matter lesions in patients with multiple sclerosis and Fabry disease

Objective

White matter lesions (WML) in multiple sclerosis (MS) differ from vascular WML caused by Fabry disease (FD). However, in atypical cases the discrimination can be difficult and may vary between individual raters. The aim of this study was to evaluate interrater reliability of WML differentiation between MS and FD patients.

Materials and methods

Brain MRI scans of 21 patients with genetically confirmed FD were compared to 21 matched patients with MS. Pseudonymized axial FLAIR sequences were assessed by 6 blinded raters and attributed to either the MS or the FD group to investigate interrater reliability. Additionally, localization of WML was compared between the two groups.

Results

The median age of patients was 46 years (IQR 35–58). Interrater reliability was moderate with a Fleiss' Kappa of 0.45 (95%CI 0.3–0.59). Overall, 85% of all ratings in the MS group and 75% in the FD group were correct. However, only 38% of patients with MS and 33% of patients with FD were correctly identified by all 6 raters. WML involving the corpus callosum (p < 0.001) as well as juxtacortical (p < 0.001) and infratentorial lesions (p = 0.03) were more frequently observed in MS patients.

Conclusion

Interrater reliability regarding visual differentiation of WML in MS from vascular WML in FD on standard axial FLAIR images alone is only moderate, despite the distinctive features of lesions in each group.

Subsecond accurate myelin water fraction reconstruction from FAST-T2 data with 3D UNET

PURPOSE

To develop a 3D UNET convolutional neural network for rapid extraction of myelin water fraction (MWF) maps from six-echo fast acquisition with spiral trajectory and T₂ -prep data and to evaluate its accuracy in comparison with multilayer perceptron (MLP) network.

METHODS

The MWF maps were extracted from 138 patients with multiple sclerosis using an iterative three-pool nonlinear least-squares algorithm (NLLS) without and with spatial regularization (srNLLS), which were used as ground-truth labels to train, validate, and test UNET and MLP networks as a means to accelerate data fitting. Network testing was performed in 63 patients with multiple sclerosis and a numerically simulated brain phantom at SNR of 200, 100 and 50.

RESULTS

Simulations showed that UNET reduced the MWF mean absolute error by 30.1% to 56.4% and 16.8% to 53.6% over the whole brain and by 41.2% to 54.4% and 21.4% to 49.4% over the lesions for predicting srNLLS and NLLS MWF, respectively, compared to MLP, with better performance at lower SNRs. UNET also outperformed MLP for predicting srNLLS MWF in the in vivo multiple-sclerosis brain data, reducing mean absolute error over the whole brain by 61.9% and over the lesions by 67.5%. However, MLP yielded 41.1% and 51.7% lower mean absolute error for predicting in vivo NLLS MWF over the whole brain and the lesions, respectively, compared with UNET. The whole-brain MWF processing time using a GPU was 0.64 seconds for UNET and 0.74 seconds for MLP.

CONCLUSION

Subsecond whole-brain MWF extraction from fast acquisition with spiral trajectory and T₂ -prep data using UNET is feasible and provides better accuracy than MLP for predicting MWF output of srNLLS algorithm.

Automatic deep learning multicontrast corpus callosum segmentation in multiple sclerosis

BACKGROUND AND PURPOSE

Corpus callosum (CC) atrophy is predictive of future disability in multiple sclerosis (MS). However, current segmentation methods are either labor- or computationally intensive. We therefore developed an automated deep learning-based CC segmentation tool and hypothesized that its output would correlate with disability.

METHODS

A cohort of 631 MS patients (449 females, baseline age 41 ± 11 years) with both 3-dimensional T1-weighted and T2-weighted fluid-attenuated inversion recovery (FLAIR) MRI was used for the development. Data from 204 patients were manually segmented to train convolutional neural networks in extracting the midsagittal intracranial and CC areas. Remaining data were used to compare segmentations with FreeSurfer and benchmark the outputs with regard to clinical correlations. A 1.5 and 3 Tesla reproducibility cohort of 9 MS patients evaluated the segmentation robustness.

RESULTS

The deep learning-based tool was accurate in selecting the appropriate slice for segmentation (98% accuracy within 3 mm of the manual ground truth) and segmenting the CC (Dice coefficient .88-.91) and intracranial areas (.97-.98). The accuracy was lower with higher atrophy. Reproducibility was excellent (intraclass correlation coefficient > .90) for T1-weighted scans and moderate-good for FLAIR (.74-.75). Segmentations were associated with baseline and future (average follow-up time 6-7 years) Expanded Disability Status Scale (ρ = -.13 to -.24) and Symbol Digit Modalities Test (r = .18-.29) scores.

CONCLUSIONS

We present a fully automatic deep learning-based CC segmentation tool optimized to modern imaging in MS with clinical correlations on par with computationally expensive alternatives.

Cerebrospinal fluid evaluation in patients with progressive motor impairment due to critical central nervous system demyelinating lesions

Background

Elevated intrathecal immunoglobulin G (IgG; oligoclonal bands (OCBs)) or IgG in people with progressive motor impairment due to “critical” demyelinating lesions are of uncertain significance.

Objective

Compare clinical/radiological features of people with “critical” demyelinating lesion-induced progressive motor impairment with/without elevated intrathecal IgG synthesis.

Methods

A total of 133 people with progressive motor impairment attributable to “critical” demyelinating lesions (corticospinal tract location, consistent with the progressive motor deficit) were compared regarding clinical and radiological presentation with and without ≥2 unique cerebrospinal fluid (CSF) OCB and/or IgG index ≥0.85.

Results

Ninety-eight (74%) had CSF-elevated OCB and/or IgG index, higher with increased magnetic resonance imaging-lesion burden. No differences were found with/without CSF abnormalities in sex (46 of 98 female (47%) vs. 22 of 35 (63%), p = 0.11), onset-age (median 49 vs. 50 years, p = 0.5), progression from onset (62 of 98 (63%) vs. 25 of 35 (71%)), progression post-relapse (36 of 98 (37%) vs. 10 of 35 (29%), p = 0.4), and duration between demyelinating disease onset and CSF examination (30 (0–359) vs. 48 (0–323) months p = 0.7). “Critical” lesions were radiologically similar, most commonly cervical spine located (72 of 98 (74%) vs. 19 of 35 (54%), p = 0.18) both with/without CSF abnormalities.

Conclusions

People with “critical” demyelinating lesion-induced progressive motor impairment typically have elevated intrathecal IgG (OCB and/or IgG) and similar clinical and radiological presentation regardless of CSF findings, therefore representing valid presentations of progressive demyelinating disease.

Constructing a Multiple Sclerosis Diagnosis Model Based on Microarray

Introduction

Multiple sclerosis is an immune-mediated demyelinating disorder of the central nervous system. Because of the complexity of etiology, pathology, clinical manifestations, and the diversity of classification, the diagnosis of MS is very difficult. We found that McDonald Criteria is very strict and relies heavily on the evidence for DIS and DIT. Therefore, we hope to find a new method to supplement the evidence and improve the accuracy of MS diagnosis.

Results

We finally selected GSE61240, GSE18781, and GSE185047 based on the GPL570 platform to build a diagnosis model. We initially selected 54 MS susceptibility locus genes identified by IMSGC and WTCCC2 as predictors for the model. After Random Forests and other series of screening, the logistic regression model was established with 4 genes as the final predictors. In external validation, the model showed high accuracy with an AUC of 0.96 and an accuracy of 86.30%. Finally, we established a nomogram and an online prediction tool to better display the diagnosis model.

Conclusion

The diagnosis model based on microarray data in this study has a high degree of discrimination and calibration in the validation set, which is helpful for diagnosis in the absence of evidence for DIS and DIT. Only one SLE case was misdiagnosed as MS, indicating that the model has a high specificity (93.93%), which is useful for differential diagnosis. The significance of the study lies in proving that it is feasible to identify MS by peripheral blood RNA, and the further application of the model and be used as a supplement to McDonald Criteria still need to be trained with larger sample size.

Case Report: Clinical and Imaging Characteristics of a Patient with Anti-flotillin Autoantibodies: Neuromyelitis Optica or Multiple Sclerosis?

Background

Demyelination diseases are complex puzzles that are not always straightforward to diagnose. Multiple sclerosis and neuromyelitis optica are two that are frequently encountered. Numerous autoantibodies newly discovered in recent years have significantly aided clinical reasoning and diagnosis in differentiating demyelination disorders. Here we report a case of demyelination disease with anti-flotillin autoantibodies positive, which is not common in past references.

Case summary

The patient presented with characteristic neuromyelitis optica symptoms and had remission and relapse. But his images exhibited characteristics of both neuromyelitis optica spectrum illness and multiple sclerosis.

Conclusion

This is the first case report describing the clinical course and imaging characteristics of demyelination illness associated with anti-flotillin autoantibodies. Although so far it appears to be a subtype of multiple sclerosis, there is still a potential that it is separate from MS and NMOSD.

Iron Rims in Patients With Multiple Sclerosis as Neurodegenerative Marker? A 7-Tesla Magnetic Resonance Study

Introduction: Multiple sclerosis (MS) is a demyelinating and neurodegenerative disease of the central nervous system, characterized by inflammatory-driven demyelination. Symptoms in MS manifest as both physical and neuropsychological deficits. With time, inflammation is accompanied by neurodegeneration, indicated by brain volume loss on an MRI. Here, we combined clinical, imaging, and serum biomarkers in patients with iron rim lesions (IRLs), which lead to severe tissue destruction and thus contribute to the accumulation of clinical disability.

Objectives: Subcortical atrophy and ventricular enlargement using an automatic segmentation pipeline for 7 Tesla (T) MRI, serum neurofilament light chain (sNfL) levels, and neuropsychological performance in patients with MS with IRLs and non-IRLs were assessed.

Methods: In total 29 patients with MS [15 women, 24 relapsing-remitting multiple sclerosis (RRMS), and five secondary-progressive multiple sclerosis (SPMS)] aged 38 (22–69) years with an Expanded Disability Status Score of 2 (0–8) and a disease duration of 11 (5–40) years underwent neurological and neuropsychological examinations. Volumes of lesions, subcortical structures, and lateral ventricles on 7-T MRI (SWI, FLAIR, and MP2RAGE, 3D Segmentation Software) and sNfL concentrations using the Simoa SR-X Analyzer in IRL and non-IRL patients were assessed.

Results: (1) Iron rim lesions patients had a higher FLAIR lesion count (p = 0.047). Patients with higher MP2Rage lesion volume exhibited more IRLs (p <0.014) and showed poorer performance in the information processing speed tested within 1 year using the Symbol Digit Modalities Test (SDMT) (p <0.047). (2) Within 3 years, patients showed atrophy of the thalamus (p = 0.021) and putamen (p = 0.043) and enlargement of the lateral ventricles (p = 0.012). At baseline and after 3 years, thalamic volumes were lower in IRLs than in non-IRL patients (p = 0.045). (3) At baseline, IRL patients had higher sNfL concentrations (p = 0.028). Higher sNfL concentrations were associated with poorer SDMT (p = 0.004), regardless of IRL presence. (4) IRL and non-IRL patients showed no significant difference in the neuropsychological performance within 1 year.

Conclusions: Compared with non-IRL patients, IRL patients had higher FLAIR lesion counts, smaller thalamic volumes, and higher sNfL concentrations. Our pilot study combines IRL and sNfL, two biomarkers considered indicative for neurodegenerative processes. Our preliminary data underscore the reported destructive nature of IRLs.

Utility of paramagnetic rim lesions on 1.5-T susceptibility phase imaging for the diagnosis of pediatric multiple sclerosis

BACKGROUND

Studies have suggested that paramagnetic rim lesions on 7-tesla (T) and 3-T susceptibility-based brain MRI are specific features of multiple sclerosis (MS) lesions in adults.

OBJECTIVE

The aim of this study was to investigate whether the presence of paramagnetic rim lesions on 1.5-T phase images can help discriminate pediatric patients with MS from those with other demyelinating diseases.

MATERIALS AND METHODS

In this retrospective study we reviewed brain MRIs performed on 1.5-T scanners that included susceptibility-weighted imaging (SWI) sequences with phase images in children younger than 18 years diagnosed with MS and other acquired demyelinating syndromes. In each case, five white matter lesions were selected using T2/fluid-attenuated inversion recovery images for further paramagnetic rim evaluation on SWI. Two researchers performed independent assessments of the presence of paramagnetic rim lesions. Discrepancies between them were settled by consensus, with input from a senior neuroradiologist.

RESULTS

We included 13 children diagnosed with MS and 16 children diagnosed with non-MS demyelinating diseases and analyzed a total of 132 focal white matter lesions. Seventy-one percent of the lesions in the MS group had paramagnetic rims, while none of the lesions in the non-MS group had rims. All but one of the children with MS had at least one lesion with a paramagnetic rim. The presence of one lesion with a paramagnetic rim on 1.5-T phase-contrast images resulted in 70% sensitivity and 100% specificity for MS.

CONCLUSION

Paramagnetic rim lesions detected on 1.5-T phase-contrast MR images can help discriminate MS from other acquired demyelinating syndromes in the pediatric population.

The usefulness of visual evoked potentials in the assessment of the pediatric multiple sclerosis

BACKGROUND

To evaluate the significance of visual evoked potentials (VEP) in the early diagnosis of optic neuritis (ON) and detecting clinically silent lesions in pediatric multiple sclerosis (PedMS). This study represents one of the largest series of PedMS which evaluated characteristics of VEP in PedMS patients.

METHODS

This was a retrospective study on 52 PedMS patients, aged 7-17 years. VEP analysis were done for all patients, after the first attack of disease and were compared to control subjects according to the pattern-reversal VEP findings.

RESULTS

The mean age of patients was 15.65 ± 1.89 years with male to female ratio of 16 (30.8%): 36 (69.2%). All of the patients had a relapsing-remitting course of the disease. ON was discovered on the initial attack in 18 (34.6%) patients, while 30 (57.7%) patients had ON in the second attack. Pathological VEP findings were present in 40 (76.9%) patients, of which 22 (42.3%) PedMS patients had clinically silent lesions. Prolonged latency of P100 waves in the PedMS group was statistically significant when compared to control subjects. The amplitude N1P1 showed a correlation with residual visual deficit.

CONCLUSION

Our results show that ON is a common initial manifestation of PedMS in the Serbian PedMS population. The prolonged P100 latency is the main indicator of ON. VEP is an objective, fast and accessible diagnostic method for detecting clinical and subclinical lesions. Thus, VEP deserves evaluation to be considered as an additional criterion for PedMS diagnosis.

Factors driving delayed time to multiple sclerosis diagnosis: Results from a population-based study

BACKGROUND

Multiple sclerosis (MS) is a highly complex chronic inflammatory disease, in which a diagnostic delay could reduce the available therapeutic options. Our aim was to identify factors contributing to diagnostic delay in a MS population living in the municipality of Biancavilla.

METHODS

This retrospective population-based study consecutively selected patients with MS diagnosed from 1992 to 2018 and resident in the city of Biancavilla. Socio-demographic and clinical data were collected through the iMed database. Date of final MS diagnosis was obtained and diagnostic delay was calculated.

RESULTS

A total of 70 patients (66.7% women) were found affected by MS according to the 2011 McDonald criteria in the municipality of Biancavilla in the period between 2005 and 2010. The mean diagnostic delay in the MS cohort of Biancavilla was 33.8 ± 56 months [median 19.5, range 1-315]. The multivariate logistic regression confirmed that age ≥ 40 years, lower educational level (1-5 years) and motor symptoms at onset were associated to longer diagnostic delay.

CONCLUSION

In this population-based study a mean delay of about 30 months occurred between initial symptoms and the MS diagnosis. Older age at onset, lower education level and motor symptoms at onset were associated to longer MS diagnostic delay.

The Role of Molecular Imaging as a Marker of Remyelination and Repair in Multiple Sclerosis

The appearance of new disease-modifying therapies in multiple sclerosis (MS) has revolutionized our ability to fight inflammatory relapses and has immensely improved patients’ quality of life. Although remarkable, this achievement has not carried over into reducing long-term disability. In MS, clinical disability progression can continue relentlessly irrespective of acute inflammation. This “silent” disease progression is the main contributor to long-term clinical disability in MS and results from chronic inflammation, neurodegeneration, and repair failure. Investigating silent disease progression and its underlying mechanisms is a challenge. Standard MRI excels in depicting acute inflammation but lacks the pathophysiological lens required for a more targeted exploration of molecular-based processes. Novel modalities that utilize nuclear magnetic resonance’s ability to display in vivo information on imaging look to bridge this gap. Displaying the CNS through a molecular prism is becoming an undeniable reality. This review will focus on “molecular imaging biomarkers” of disease progression, modalities that can harmoniously depict anatomy and pathophysiology, making them attractive candidates to become the first valid biomarkers of neuroprotection and remyelination.

Direct imaging of white matter ultrashort T2∗ components at 7 Tesla

PURPOSE

To demonstrate direct imaging of the white matter ultrashort T₂^∗ components at 7 Tesla using inversion recovery (IR)-enhanced ultrashort echo time (UTE) MRI. To investigate its characteristics, potentials and limitations, and to establish a clinical protocol.

MATERIAL AND METHODS

The IR UTE technique suppresses long T₂^∗ signals within white matter by using adiabatic inversion in combination with dual-echo difference imaging. Artifacts arising at 7 T from long T₂^∗ scalp fat components were reduced by frequency shifting the IR pulse such that those frequencies were inverted likewise. For 8 healthy volunteers, the T₂^∗ relaxation times of white matter were then quantified. In 20 healthy volunteers, the UTE difference and fraction contrast were evaluated. Finally, in 6 patients with multiple sclerosis (MS), the performance of the technique was assessed.

RESULTS

A frequency shift of -1.2 ppm of the IR pulse (i.e. towards the fat frequency) provided a good suppression of artifacts. With this, an ultrashort compartment of (68 ± 6) % with a T₂^∗ time of (147 ± 58) μs was quantified with a chemical shift of (-3.6 ± 0.5) ppm from water. Within healthy volunteers' white matter, a stable ultrashort T₂^∗ fraction contrast was calculated. For the MS patients, a significant fraction reduction in the identified lesions as well as in the normal-appearing white matter was observed.

CONCLUSIONS

The quantification results indicate that the observed ultrashort components arise primarily from myelin tissue. Direct IR UTE imaging of the white matter ultrashort T₂^∗ components is thus feasible at 7 T with high quantitative inter-subject repeatability and good detection of signal loss in MS.

Diagnostic value of gadolinium contrast administration for spinal cord magnetic resonance imaging in multiple sclerosis patients and correlative markers of lesion enhancement

Background

Magnetic resonance imaging is essential for monitoring people with multiple sclerosis, but the diagnostic value of gadolinium contrast administration in spine magnetic resonance imaging is unclear.

Objective

To assess the diagnostic value of gadolinium contrast administration in spine magnetic resonance imaging follow-up examinations and identify imaging markers correlating with lesion enhancement.

Methods

A total of 65 multiple sclerosis patients with at least 2 spinal magnetic resonance imaging follow-up examinations were included. Spine magnetic resonance imaging was performed at 3 Tesla with a standardized protocol (sagittal and axial T2-weighted turbo spin echo and T1-weighted post-contrast sequences). T2 lesion load and enhancing lesions were assessed by two independent neuroradiologists for lesion size, localization, and T2 signal ratio (T2 signal_lesion/T2 signal_{normal appearing spinal cord}).

Results

A total of 68 new spinal T2 lesions and 20 new contrast-enhancing lesions developed during follow-up. All enhancing lesions had a discernable correlate as a new T2 lesion. Lesion enhancement correlated with a higher T2 signal ratio compared to non-enhancing lesions (T2 signal ratio: 2.0 ± 0.4 vs. 1.4 ± 0.2, ****p < 0.001). Receiver operating characteristics analysis showed an optimal cutoff value of signal ratio 1.78 to predict lesion enhancement (82% sensitivity and 97% specificity).

Conclusion

Gadolinium contrast administration is dispensable in follow-up spine magnetic resonance imaging if no new T2 lesions are present. Probability of enhancement correlates with the T2 signal ratio.

Validation of MRI radiological reports in pediatric MS according to the McDonald 2017 criteria: A Danish nationwide multicenter cohort study

BACKGROUND

MRI allows demonstration of dissemination in space and time at the first demyelinating event. However, no pediatric MS study has investigated the validity of MS-specific outcomes described in MRI radiological reports that clinicians rely on to make the MS diagnosis and to assess the MS treatment effect. Our aim was to validate MS-specific outcomes in hospital MRI reports in pediatric MS by comparing MS-specific outcomes in MRI reports with secondary MRI review.

METHODS

A senior consultant and a resident neurologist extracted data on MS-specific outcomes from MRI reports at baseline and follow-up in children with MS onset during 2008-15 in Denmark. Gold standard was an expert neuroradiologist's secondary MRI review. We estimated percent agreement and Kappa values by comparing data extracted from hospital MRI reports (what we wanted to test) with results from the secondary MRI reviews (our gold standard).

RESULTS

Among 55 children with MS, we included 44 baseline and 48 follow-up MRIs. The median age at MS onset was 16.3 years (range 9.2‒17.9). Agreement between the MRI reports and the secondary MRI review ranged 68%-100% for MS-specific outcomes; agreement was higher when MRI outcomes were present. Kappa values ranged from 0.42 ("moderate") to 1.00 ("excellent"). Kappa for fulfillment of the McDonald 2017 criteria was 0.60 on baseline MRI, and 0.53 on follow-up MRI. Kappa for a new lesion on follow-up MRI was 0.41.

CONCLUSION

Agreement was moderate to good for most MS-specific outcomes between MS neurologists' data extraction from hospital MRI radiological reports compared with a neuroradiologist's secondary MRI review. The agreement was moderate for both fulfilling the McDonald 2017 criteria and acquiring a new lesion on follow-up MRI. We recommend structured MRI reporting in children suspected of acquired demyelinating syndromes to increase validity of hospital MRI reports and clinical use.

Correlation of cortical lesions of multiple sclerosis at double inversion recovery with cognition screening scores

Background

Multiple sclerosis is a chronic inflammatory disease affecting both white and gray matters of the central nervous system. It has been approved that the degree of gray matter involvement is closely associated with the degree of physical disability and the extent of cognitive impairment. Thus, it is necessary to incorporate widely available simple methods for neurocognitive evaluation and gray matter detection in the periodic assessment of MS patients that will influence treatment decisions.

Objectives

To assess the correlation of cortical lesions of multiple sclerosis (MS) at double inversion recovery (DIR) with cognition screening scores

Methods

This study was conducted on 30 patients with MS with an average age of 31.3±13.6 years. All of them underwent MRI and clinical assessment with the calculation of Expanded Disability Status Scale (EDSS), Montreal Cognitive Assessment (MoCA), and Symbol Digit Modality Test (SDMT) scores. The image analysis was performed by 2 reviewers for cortical lesion number, shape, and subtypes, and total lesion load.

Results

Both MoCA and SDMT scales had a significant inverse correlation with cortical lesions number (r=− 0.68, − 0.72) respectively and total lesion load (r=− 0.53, − 0.65) respectively. Besides, there was a significant inverse correlation between the MoCA test, varied cortical subtypes: leukocortical, juxtacortical, and intracortical subtypes (r = − 0.63, − 0.56, − 0.52) respectively, and different cortical lesion shapes: oval, wedge, and curvilinear shaped (r = − 0.62, − 0.69, − 0.49) respectively. As well, the SDMT scale showed a significant inverse correlation with varied cortical subtypes: intracortical, leukocortical, and juxtacortical subtypes (r = − 0.63, − 0.61, − 0.57) respectively, and different cortical lesion shapes: oval, curvilinear, and wedge shaped (r = − 0.61, − 0.59, − 0.46) respectively. Interestingly, there was an excellent inter-observer correlation of cortical lesion number (r = 0.96), total lesion load (r = 0.95), subtypes of cortical lesion (r = 0.94), and cortical lesion shapes (r = 0.77).

Conclusion

We concluded that DIR can detect cortical lesions of MS, and MRI findings were well-correlated with cognitive dysfunction in these patients.

Long-term outcomes in patients presenting with optic neuritis: Analyses of the MSBase registry

BACKGROUND

Short-term outcomes of optic neuritis (ON) have been well characterized. Limited data exists on longer-term visual outcomes in patients who present with ON. The large MSBase registry allows for characterization of long-term visual outcomes after ON.

METHODS

Via the MSBase Registry, data on patients from 41 centers was collected during routine clinical and research visits. Physical and visual disability were measured using the expanded disability status scale (EDSS) and the visual function score (VFS). Inclusion criteria for this analysis included age ≥ 18 years, clinically isolated syndrome (CIS), ON-onset, baseline visit within 6 months of onset, and at least one follow-up visit. Survival analysis was used to evaluate the association of disease-modifying treatment with time to conversion to clinically definite MS or sustained EDSS/VFS progression.

RESULTS

Data from 60,933 patients were obtained from the MSBase registry in July 2019. Of these, 1317 patients met inclusion criteria; 935 were treated at some point in disease course, while 382 were never treated. At baseline, mean age was 32.3 ± 8.8 years, 74% were female, median EDSS was 2 (IQR 1-2), and median VFS was 1 (IQR 0-2). Median follow-up time was 5.2 years (IQR 2.4-9.3). Treatment was associated with reduced risk and delayed conversion to clinically definite MS (HR = 0.70, p < 0.001), sustained EDSS progression (HR = 0.46, p < 0.0001) and sustained VFS (HR = 0.41, p < 0.001) progression.

CONCLUSIONS

In the MSBase cohort, treatment after ON was associated with better visual and neurological outcomes compared to no treatment. These results support early treatment for patients presenting with ON as the first manifestation of MS.

Radiological and Laboratory Features of Multiple Sclerosis Patients With Immunosuppressive Therapy: A Multicenter Retrospective Study in Japan

Background: Multiple sclerosis (MS) is a relapsing, inflammatory, and demyelinating disease of central nervous system showing marked clinical heterogeneity. Many factors might influence the choice of relapse prevention drug, and treatment response varies among patients. Despite the enlargement of disease-modifying drugs for MS (MS-DMDs), some patients have been treated with corticosteroid and/or immunosuppressant (CS/IS).

Objective: To clarify the radiological and laboratory features of MS treated with CS/IS for relapse prevention.

Methods: Clinical records including radiological and laboratory findings, and drugs used for relapse prevention were reviewed retrospectively.

Results: Out of 92 consecutive MS patients, 25 (27%) were treated with CS/IS. The followings were observed less frequently in patients treated with CS/IS than in those with MS-DMDs: three or more periventricular lesions, ovoid lesions, subcortical lesions, typical contrast-enhancing lesions, negative for serum autoantibodies, and positive for oligoclonal bands in the cerebrospinal fluid. Multiple logistic regression analysis revealed that the absence of typical contrast-enhancing lesions and positivity for serum autoantibodies were independent factors associated with CS/IS prescription (odds ratio 25.027 and 14.537, respectively).

Conclusion: In this cohort of Japanese patients clinically diagnosed with MS, radiological and serological findings atypical of MS were observed more frequently in patients treated with CS/IS than in those with MS-DMDs as a part of MS therapy. The absence of contrast-enhancing lesions typical of MS and positivity for serum autoantibodies were independent factors strongly associated with CS/IS use.

New Prospects for Ultra-High-Field Magnetic Resonance Imaging in Multiple Sclerosis

ABSTRACT

There is growing interest in imaging multiple sclerosis (MS) through the ultra-high-field (UHF) lens, which currently means a static magnetic field strength of 7 T or higher. Because of higher signal-to-noise ratio and enhanced susceptibility effects, UHF magnetic resonance imaging improves conspicuity of MS pathological hallmarks, among them cortical demyelination and the central vein sign. This could, in turn, improve confidence in MS diagnosis and might also facilitate therapeutic monitoring of MS patients. Furthermore, UHF imaging offers unique insight into iron-related pathology, leptomeningeal inflammation, and spinal cord pathologies in neuroinflammation. Yet, limitations such as the longer scanning times to achieve improved resolution and incipient safety data on implanted medical devices need to be considered. In this review, we discuss applications of UHF imaging in MS, its advantages and limitations, and practical aspects of UHF in the clinical setting.

Performance of the 2017 and 2010 Revised McDonald Criteria in Predicting MS Diagnosis After a Clinically Isolated Syndrome: A MAGNIMS Study

BACKGROUND AND OBJECTIVES

To compare the performance of the 2017 revisions to the McDonald criteria with the 2010 McDonald criteria in establishing MS diagnosis and predicting prognosis in patients with clinically isolated syndrome (CIS) suggestive of multiple sclerosis (MS).

METHODS

CSF examination, brain and spinal cord MRI obtained ≤5 months from CIS onset, and a follow-up brain MRI acquired within 15 months from CIS onset were evaluated in 785 CIS patients from 9 European centers. Date of second clinical attack and of reaching Expanded Disability Status Score (EDSS) ≥ 3.0, if they occurred, were also collected. Performance of the 2017 and 2010 McDonald criteria for dissemination in space (DIS), time (DIT) (including oligoclonal bands assessment) and DIS + DIT for predicting a second clinical attack (clinically definite [CD] MS) and EDSS ≥ 3.0 at follow-up was evaluated. Time to MS diagnosis for the different criteria was also estimated.

RESULTS

At follow-up (median = 69.1 months), 406/785 CIS patients developed CDMS. At 36 months, the 2017 DIS + DIT criteria had higher sensitivity (0.83 vs 0.66), lower specificity (0.39 vs 0.60) and similar area under the curve values (0.61 vs 0.63). Median time to MS diagnosis was shorter with the 2017 vs the 2010 or CDMS criteria (2017 revision = 3.2; 2010 revision = 13.0; CDMS = 58.5 months). The 2 sets of criteria similarly predicted EDSS ≥ 3.0 milestone. Three periventricular lesions improved specificity in patients ≥45 years.

DISCUSSION

The 2017 McDonald criteria showed higher sensitivity, lower specificity and similar accuracy in predicting CDMS compared to 2010 McDonald criteria, while shortening time to diagnosis of MS.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that the 2017 McDonald Criteria more accurately distinguish CDMS in patients early after a CIS when compared to the 2010 McDonald criteria.

Relayed nuclear Overhauser effect weighted (rNOEw) imaging identifies multiple sclerosis

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system in which the immune system attacks the myelin and axons, consequently leading to demyelination and axonal injury. Magnetic resonance imaging (MRI) plays a pivotal role in the diagnosis of MS, and currently various types of MRI techniques have been used to detect the pathology of MS based on unique mechanisms. In this study, we applied the relayed nuclear Overhauser effect weighted (rNOEw) imaging to study human MS at clinical 3T. Three groups of subjects, including 20 normal control (NC) subjects, 14 neuromyelitis optica spectrum disorders (NMOSD) patients and 21 MS patients, were examined at a clinical 3T MRI scanner. Whole-brain rNOEw images of each subject were obtained by acquiring a control and a labeled image within four minutes. Significantly lower brain rNOEw contrast was detected in MS group compared to NC (P = 0.008) and NMOSD (P = 0.014) groups, while no significant difference was found between NC and NMOSD groups (P = 0.939). The lower rNOEw contrast of MS group compared to NC/NMOSD group was significant in white matter (P = 0.041/0.021), gray matter (P = 0.004/0.020) and brain parenchyma (P = 0.015/0.021). Moreover, MS lesions showed higher number and larger size but lower rNOEw contrast than NMOSD lesions (P = 0.002). Our proposed rNOEw imaging scheme has potential to serve as a new method for assisting MS diagnosis. Importantly, it may be used to identify MS from NMOSD.